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ssuvetha
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Model Details
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ssuvetha
Model Tree
TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
Input Modalities
Output Modalities
Supported Functionality
This repository contains a LoRA adapter trained on pharmaceutical domain text using QLoRA.
Base model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
This is non-instruction fine-tuning (continued pretraining / domain adaptation), not chat fine-tuning.
The model was trained as a causal language model on cleaned pharma-domain text extracted from a PDF corpus. Its objective is next-token prediction in the pharmaceutical domain.
This adapter is intended for:
python
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfigfrom peft import PeftModelimport torchbase_model_id = "TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T"adapter_id = "ssuvetha/pharma-tinyllama-domain-lora"tokenizer = AutoTokenizer.from_pretrained(adapter_id)bnb_config = BitsAndBytesConfig(load_in_4bit=True,bnb_4bit_quant_type="nf4",bnb_4bit_compute_dtype=torch.float16,bnb_4bit_use_double_quant=True,)base_model = AutoModelForCausalLM.from_pretrained(base_model_id,quantization_config=bnb_config,device_map="auto",)model = PeftModel.from_pretrained(base_model, adapter_id)model.eval()